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Smart Dam: Upstream Sensing, Hydro-Blockchain, and Flood Feature Extractions for Dam Inflow Prediction

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Advances in Information and Communication (FICC 2020)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 1129))

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Abstract

Heavy rain occurs frequently during extreme weather, and the associated resultant flood damage represents a social problem. The present study aims to redefine the dam watershed as a smart dam and attempts to systematize the technology for flood prediction by integrating upstream sensing, dam inflow prediction, and a hydro-blockchain. In order to detect high water levels, we devise an upstream sensing method to observe the water level at the uppermost stream of a dam watershed, and summarize potential implementation hurdles. We also propose a hydro-blockchain configuration that provides a basis for the fair transaction of water rights. We implement a field study in the Kanto region, Japan, to observe the upstream water level using the devised water level sensor. We analyze the relationship between the measured water levels and the dam inflow and also analyze the response of the time difference. Furthermore, we propose a flood-feature extraction using a 20 year hydro-dataset of rainfall and water levels, and propose dam inflow prediction models using various time series machine learning algorithms. We demonstrate the application of our model results and discuss their usefulness.

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Acknowledgments

We thank Mr. Shinichi Kuramoto and Mr. Takuji Fukumoto (MathWorks Japan) for providing stable resources for machine and deep learning.

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Authors and Affiliations

  1. Research Institute for Infra. Paradigm Shift, 5-20-8 Asakusabashi Taito-ku, Tokyo, Japan

    Takato Yasuno, Akira Ishii, Masazumi Amakata & Junichiro Fujii

Authors
  1. Takato Yasuno
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  2. Akira Ishii
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  3. Masazumi Amakata
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  4. Junichiro Fujii
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Corresponding author

Correspondence to Takato Yasuno .

Editor information

Editors and Affiliations

  1. Faculty of Science and Engineering, Saga University, Saga, Japan

    Kohei Arai

  2. The Science and Information (SAI) Organization, Bradford, West Yorkshire, UK

    Supriya Kapoor

  3. The Science and Information (SAI) Organization, Bradford, West Yorkshire, UK

    Rahul Bhatia

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Yasuno, T., Ishii, A., Amakata, M., Fujii, J. (2020). Smart Dam: Upstream Sensing, Hydro-Blockchain, and Flood Feature Extractions for Dam Inflow Prediction. In: Arai, K., Kapoor, S., Bhatia, R. (eds) Advances in Information and Communication. FICC 2020. Advances in Intelligent Systems and Computing, vol 1129. Springer, Cham. https://doi.org/10.1007/978-3-030-39445-5_12

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